Embodiments of the invention relate generally to tomographic imaging and, more particularly, to an apparatus and method for wide cone helical reconstruction.
Typically, in x-ray systems, such as computed tomography (CT) imaging systems, an x-ray source emits a fan-shaped or cone-shaped beam toward a subject, such as a patient, a piece of luggage, or any other object of interest. Hereinafter, the terms “subject” and “object” shall include anything capable of being imaged. The beam, after being attenuated by the subject, impinges upon an array of radiation detectors. The intensity of the attenuated beam of radiation received at the detector array is typically dependent upon the attenuation of the x-ray beam by the subject. Each detector element of the detector array produces an electrical signal indicative of the attenuated beam received by the detector element. The electrical signals are converted to digital signals and transmitted to a data processing system for analysis, which ultimately produces an image.
Generally, the x-ray source and the detector array are rotated about the gantry within an imaging plane and around the subject. X-ray sources typically include x-ray tubes, which emit the x-ray beam from a focal point. X-ray detectors typically include a collimator for collimating x-ray beams directed toward the detector, a scintillator adjacent to the collimator for converting x-rays to light energy, and photodiodes for receiving the light energy from the scintillator and producing electrical signals therefrom. Typically, each scintillator of a scintillator array converts x-rays to light energy and discharges the light energy to a photodiode adjacent thereto. Each photodiode detects the light energy and generates a corresponding electrical signal. The outputs of the photodiodes are digitized and then transmitted to the data processing system for image reconstruction.
The helical scan is a popular scan mode in clinical computed tomography (CT) diagnostic imaging due to its fast volumetric coverage capability. Traditionally, known algorithms such as Feldkamp-Davis-Kress algorithms (FDK-type algorithms) have been widely used because of the simplicity of the FDK-type algorithms and the desirable image characteristics they produce. However, as the detector size in the Z-direction (or slice direction) in CT applications has increased in recent years, helical reconstruction has become more challenging for FDK-type and other known algorithms due to the increased cone angle in the X-ray beam. Traditional view weighting methods are insufficient to address the increased cone beam artifacts while maintaining the desired noise statistics.
Recently, theoretically exact algorithms have been proposed for helical reconstruction. These types of algorithms can generate a reconstruction image (we use the term image to represent both a 2D image which is a single slice image and a 3D image which is an image volume, hereafter) with little or no cone beam artifacts, however, they also lead to higher noise level due to the difficulty in handling redundant data. More recently, iterative reconstruction (IR) algorithms have also been proposed for CT reconstruction that show great promise in reducing both noise and cone-beam artifacts. However, IR algorithms generally are associated with a significant computational penalty and therefore the reconstruction is much slower than other methods.
Therefore, a new reconstruction approach is desirable for wide cone helical scans having low cone beam artifacts while maintaining simplicity and low noise level.